Landmarking

Sold as an easy but less revealing alternative to the multistate model approach, the landmarking approach picks a grid of time points and, using the risk set at that time, calculates the Cox regression upto some set time horizon. Some function of the fitted betas in the additive model is used to link the separate fits e.g. a linear combination. I've been going off this paper.

As with the etm, I've just used some sample data from the IMPACT clinical model to try this method out.

So far, I've used R to produce the Cox regressions at each landmark point but the paper then generated predictions of the survival probabilities from these point by estimating the baseline hazard (and so baseline cumulative hazard) to go with the regression parameters.

I thought I'd run the multistate model code with the RR/hazard adjustments for interventions from the IMPACT paper and try and recreate the same figures. So these are the proportions of incident cases that die from each outcome. Then I could repeat this, with my code, at different landmark time points and see how the hazard ratios change.